Artificial Intelligence Software Structured to Simulate Human Working Memory, Mental Imagery, and Mental Continuity
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arXiv
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| Format: | Preprint |
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2022
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| _version_ | 1866910016867401728 |
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| author | Reser, Jared Edward |
| author_facet | Reser, Jared Edward |
| contents | This article presents an artificial intelligence (AI) architecture intended to simulate the iterative updating of the human working memory system. It features several interconnected neural networks designed to emulate the specialized modules of the cerebral cortex. These are structured hierarchically and integrated into a global workspace. They are capable of temporarily maintaining high-level representational patterns akin to the psychological items maintained in working memory. This maintenance is made possible by persistent neural activity in the form of two modalities: sustained neural firing (resulting in a focus of attention) and synaptic potentiation (resulting in a short-term store). Representations held in persistent activity are recursively replaced resulting in incremental changes to the content of the working memory system. As this content gradually evolves, successive processing states overlap and are continuous with one another. The present article will explore how this architecture can lead to iterative shift in the distribution of coactive representations, ultimately leading to mental continuity between processing states, and thus to human-like thought and cognition. Taken together, these components outline a biologically motivated route toward synthetic consciousness or artificial sentience and subjectivity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2204_05138 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Artificial Intelligence Software Structured to Simulate Human Working Memory, Mental Imagery, and Mental Continuity Reser, Jared Edward Neurons and Cognition Artificial Intelligence Machine Learning Neural and Evolutionary Computing Symbolic Computation This article presents an artificial intelligence (AI) architecture intended to simulate the iterative updating of the human working memory system. It features several interconnected neural networks designed to emulate the specialized modules of the cerebral cortex. These are structured hierarchically and integrated into a global workspace. They are capable of temporarily maintaining high-level representational patterns akin to the psychological items maintained in working memory. This maintenance is made possible by persistent neural activity in the form of two modalities: sustained neural firing (resulting in a focus of attention) and synaptic potentiation (resulting in a short-term store). Representations held in persistent activity are recursively replaced resulting in incremental changes to the content of the working memory system. As this content gradually evolves, successive processing states overlap and are continuous with one another. The present article will explore how this architecture can lead to iterative shift in the distribution of coactive representations, ultimately leading to mental continuity between processing states, and thus to human-like thought and cognition. Taken together, these components outline a biologically motivated route toward synthetic consciousness or artificial sentience and subjectivity. |
| title | Artificial Intelligence Software Structured to Simulate Human Working Memory, Mental Imagery, and Mental Continuity |
| topic | Neurons and Cognition Artificial Intelligence Machine Learning Neural and Evolutionary Computing Symbolic Computation |
| url | https://arxiv.org/abs/2204.05138 |